And in the article he shows last year's final bracket vs. his first one. Basically, whatever happens in the beginning has little relevance to the final. Although, from the beginning, he did predict we'd be in Manchester.

All right, before we go much farther with this, I have to say -- and I suspect it's already been said, but it bears repeating -- Allentown cannot host the "Midwest" Regional because Allentown is not "Midwest". Allentown is farther east than Ithaca is. It needs to be called the "Mideast" Regional.

___________________________ If you lead a good life, go to Sunday school and church, and say your prayers every night, when you die, you'll go to LYNAH!

Allentown is the Midwest Regional. The typo was that Cornell is being put in the Northeast Regional, not the Midwest.

FWIW, my bracketology came out slightly different, because I assumed that because Notre Dame was flying no matter where they went, they did not have to be in the closest regional

Worcester:
1 Notre Dame vs 16 Canisius
7 WMU vs 9 Providence

Bridgeport
2 Clarkson vs 15 Duluth
8 Minn. State vs 11 Omaha

Sioux Falls
3 St. Cloud vs 14 Minnesota
5 Ohio State vs 10 NoDak

Allentown
4 Cornell vs 13 Northeaastern
6 Denver vs 12 Penn State

Mind you, this is wishful thinking on my part, because I REALLY want us to be in Allentown, but so be it. However as long as we can stay in the top 4 and so can St. Cloud, I'd be happy since we'd never end up in Sioux Falls in that case.

Trotsky
Cornell needs to start "hosting" Albany regionals, whatever that bullsh-t entails. Ideally hosting would be banned, but while we still have this stupid system we might as well use it.

Except that Albany was most recently dismissed as a site by three NCAA. The good news is that the facility was upgraded this year. Anyone that wants to check it out can attend the Mayor's Cup this Saturday. Onion vs RIP.

It's all wrong. BC leading Hockey East is just a way to rationalize having another eastern team in the bracketology. And with BC in the bracketology, it shifts us into New England on the justification of attendance.

Jeff Hopkins '82
It's all wrong. BC leading Hockey East is just a way to rationalize having another eastern team in the bracketology. And with BC in the bracketology, it shifts us into New England on the justification of attendance.

Because current within-league standing depends partly on how many games teams have played, the methodology uses the current winning % in the league to guesstimate which team wins the league's eventual automatic bid. In this case, BC is both in first place and has the highest winning % (75.0%)1. Northeastern and Providence, the other two Hockey East teams in this week's brackets, are included because of their standing in the pairwise.

An obvious, but perhaps unavoidable, weakness of this method concerns upsets over high-ranking favorite in conference championships. The six leagues each have an auto-bid, so ten of the 16 are selected at large. But say an underdog wins a conference championship, then one of the previous favorites might bump a weaker team. E.g., BC is currently tied for 17th in the pairwise, so if the conference championship were this weekend, BC would have to win it to be included in the NCAA. If Providence (currently tied for 9th) or Northeastern (currently 13) were to win, then HE would get only 2 bids. If a team other than these two or BC (e.g., BU) were to win, then HE would still get 3 bids.

In terms of winning % in league, current conference leaders are:2 Canisius (31), Notre Dame (1), Clarkson (4t)/Cornell (1t), BC (17t), Denver (4t), and Minnesota State (6). Of these, Canisius & BC are not in the top ten, so they must win their conferences to make the NCAA's. Using today's data, the other four teams will make the tournament no matter what, because they are all in the top 10 of the pairwise. But if, say, Providence were to win the HE championship and teams outside the top 14 in pairwise win the conference championships in the B1G, ECAC, NCAC, and WCHA, this would add 4 auto-bids to the mix and bump Northeastern out of the tourney. HE would then get only one bid: Providence, attendance be damned.

1USCHO labels the column "Win %" but actually reports decimal proportions. Here I've written the number as a percentage to be consistent.

2Numbers in parentheses are ranks in the pairwise. A number followed by "t" indicates the team is tied with one or more other teams.

Swampy
In terms of winning % in league, current conference leaders are:2 Canisius (31), Notre Dame (1), Clarkson (4t)/Cornell (1t), BC (17t), Denver (4t), and Minnesota State (6). Of these, Canisius & BC are not in the top ten, so they must win their conferences to make the NCAA's.

This would be more accurately stated as "...so if the regular season ended today, they would have to win their conferences to make the NCAAs." Canisius may not have a path to an at-large, but BC certainly has the mathematical opportunity to get there, especially if there aren't any serious upsets in the conference tourney title games.

Swampy
In terms of winning % in league, current conference leaders are:2 Canisius (31), Notre Dame (1), Clarkson (4t)/Cornell (1t), BC (17t), Denver (4t), and Minnesota State (6). Of these, Canisius & BC are not in the top ten, so they must win their conferences to make the NCAA's.

This would be more accurately stated as "...so if the regular season ended today, they would have to win their conferences to make the NCAAs." Canisius may not have a path to an at-large, but BC certainly has the mathematical opportunity to get there, especially if there aren't any serious upsets in the conference tourney title games.

You are correct.

I assumed the word "current" in my first sentence made this clear: everything is based on data available today and as if the season ended today. Obviously the assumption was wrong.

Swampy
In terms of winning % in league, current conference leaders are:2 Canisius (31), Notre Dame (1), Clarkson (4t)/Cornell (1t), BC (17t), Denver (4t), and Minnesota State (6). Of these, Canisius & BC are not in the top ten, so they must win their conferences to make the NCAA's.

This would be more accurately stated as "...so if the regular season ended today, they would have to win their conferences to make the NCAAs." Canisius may not have a path to an at-large, but BC certainly has the mathematical opportunity to get there, especially if there aren't any serious upsets in the conference tourney title games.

You are correct.

I assumed the word "current" in my first sentence made this clear: everything is based on data available today and as if the season ended today. Obviously the assumption was wrong.

It was actually the word "current" that made me parse the next sentence the way I did. Doesn't matter, we agree on what the reality is.

Swampy
In terms of winning % in league, current conference leaders are:2 Canisius (31), Notre Dame (1), Clarkson (4t)/Cornell (1t), BC (17t), Denver (4t), and Minnesota State (6). Of these, Canisius & BC are not in the top ten, so they must win their conferences to make the NCAA's.

This would be more accurately stated as "...so if the regular season ended today, they would have to win their conferences to make the NCAAs." Canisius may not have a path to an at-large, but BC certainly has the mathematical opportunity to get there, especially if there aren't any serious upsets in the conference tourney title games.

You are correct.

I assumed the word "current" in my first sentence made this clear: everything is based on data available today and as if the season ended today. Obviously the assumption was wrong.

It was actually the word "current" that made me parse the next sentence the way I did. Doesn't matter, we agree on what the reality is.

I understand the basis. I just don't believe it will be worth worrying about, because I don't believe BC will be there by the end.

I'm pretty sure this playoffstatus predictor is heavily flawed. It does not appear to sufficiently account for the inherent variance of a hockey game and considers a good team losing to a lesser team an extremely unlikely event. For example, it gives Cornell a 96% chance of making Lake Placid, which is obviously absurd. It also gives Cornell a 71% chance of getting the 1-seed in the ECAC and Clarkson a 27% chance, despite only one point separating them with eight games remaining and the two teams playing each other one more time. (Plus the game is at Clarkson and Clarkson crushed us the last time we played, which I assume the model doesn't take into account.)

I'm pretty sure this playoffstatus predictor is heavily flawed. It does not appear to sufficiently account for the inherent variance of a hockey game and considers a good team losing to a lesser team an extremely unlikely event. For example, it gives Cornell a 96% chance of making Lake Placid, which is obviously absurd. It also gives Cornell a 71% chance of getting the 1-seed in the ECAC and Clarkson a 27% chance, despite only one point separating them with eight games remaining and the two teams playing each other one more time. (Plus the game is at Clarkson and Clarkson crushed us the last time we played, which I assume the model doesn't take into account.)

Can’t agree more. These “odds” sites that calculate and blend data down for any league you can think of really don’t have any insight or context baked in.

I'm pretty sure this playoffstatus predictor is heavily flawed. It does not appear to sufficiently account for the inherent variance of a hockey game and considers a good team losing to a lesser team an extremely unlikely event. For example, it gives Cornell a 96% chance of making Lake Placid, which is obviously absurd. It also gives Cornell a 71% chance of getting the 1-seed in the ECAC and Clarkson a 27% chance, despite only one point separating them with eight games remaining and the two teams playing each other one more time. (Plus the game is at Clarkson and Clarkson crushed us the last time we played, which I assume the model doesn't take into account.)

Can’t agree more. These “odds” sites that calculate and blend data down for any league you can think of really don’t have any insight or context baked in.

I assume the above problems could be fixed pretty easily by just looking at, for example, how often the #1 team in the KRACH loses to the #2 team, how often the #1 loses to the #3, and so on. And then looking at how big an advantage home ice is, on average, and factoring that in.

I'm pretty sure this playoffstatus predictor is heavily flawed. It does not appear to sufficiently account for the inherent variance of a hockey game and considers a good team losing to a lesser team an extremely unlikely event. For example, it gives Cornell a 96% chance of making Lake Placid, which is obviously absurd. It also gives Cornell a 71% chance of getting the 1-seed in the ECAC and Clarkson a 27% chance, despite only one point separating them with eight games remaining and the two teams playing each other one more time. (Plus the game is at Clarkson and Clarkson crushed us the last time we played, which I assume the model doesn't take into account.)

Can’t agree more. These “odds” sites that calculate and blend data down for any league you can think of really don’t have any insight or context baked in.

They're also not really designed to predict the probability of a particular outcome - they're designed to predict the probability of a particular outcome assuming everything between now and then pretty much goes the way it's gone up until now.

I'm pretty sure this playoffstatus predictor is heavily flawed. It does not appear to sufficiently account for the inherent variance of a hockey game and considers a good team losing to a lesser team an extremely unlikely event. For example, it gives Cornell a 96% chance of making Lake Placid, which is obviously absurd. It also gives Cornell a 71% chance of getting the 1-seed in the ECAC and Clarkson a 27% chance, despite only one point separating them with eight games remaining and the two teams playing each other one more time. (Plus the game is at Clarkson and Clarkson crushed us the last time we played, which I assume the model doesn't take into account.)

Can’t agree more. These “odds” sites that calculate and blend data down for any league you can think of really don’t have any insight or context baked in.

They're also not really designed to predict the probability of a particular outcome - they're designed to predict the probability of a particular outcome assuming everything between now and then pretty much goes the way it's gone up until now.

One nice (and probably reliable) feature is the use of red vs green, which shows what the team can control. If we win out we are guaranteed no worse than #3.

I'm pretty sure this playoffstatus predictor is heavily flawed. It does not appear to sufficiently account for the inherent variance of a hockey game and considers a good team losing to a lesser team an extremely unlikely event. For example, it gives Cornell a 96% chance of making Lake Placid, which is obviously absurd. It also gives Cornell a 71% chance of getting the 1-seed in the ECAC and Clarkson a 27% chance, despite only one point separating them with eight games remaining and the two teams playing each other one more time. (Plus the game is at Clarkson and Clarkson crushed us the last time we played, which I assume the model doesn't take into account.)

Can’t agree more. These “odds” sites that calculate and blend data down for any league you can think of really don’t have any insight or context baked in.

They're also not really designed to predict the probability of a particular outcome - they're designed to predict the probability of a particular outcome assuming everything between now and then pretty much goes the way it's gone up until now.

I don't agree at all with any of this line of criticism. Roughly in order:

1. Just because intuitions disagree with odds doesn't mean the odds are wrong or the methodology is flawed.

2. We operate with a host of perception biases and our monkey brains are notoriously terrible at assigning relative likelihoods and proportions because we are strongly influenced by anecdotal experience.

3. A model will of course "assume things keep on going as they have been" because that's the best guess of what will happen. As long as the methodologically-correct degree of uncertainty (error) is built into the model, it's doing its job right.

Why is a 96% chance of making Lake Placid "obviously" absurd? Sure, it seems high, but what it means is 19 times out of 20 team x with our profile would advance. That's still once in 20 that it doesn't. That may well be in accord with historical actuals.

The problem with models isn't modeling per se -- modeling works really well or Armstrong wouldn't have hit the moon. What matters is taking care in choosing metrics and getting the probabilities right. Statistics and probability theory have been working on each of those tasks respectively for a hundred years and as uncomfortable as it may be they now do a much, much better job of predicting than the eye test or common sense.

I think we had this discussion here last year. ... FWIW - as someone who wrote something similar for CHN (haven't published this year's yet - a couple more weeks until we do) ... I agree with everything Greg wrote. Except I also agree with some of the criticisms, in that, I certainly believe it's possible to put some better metrics into the equation and come up with a better output. Or - more precisely - I think the model could use some uncertainty fuzziness baked into it, so long as it's mathematically-based uncertainty. And that is beyond my capabilities.

So if anyone wants to contribute any formulas, code or ideas to what we're doing on CHN - feel free. All ears.

adamw
I think we had this discussion here last year. ... FWIW - as someone who wrote something similar for CHN (haven't published this year's yet - a couple more weeks until we do) ... I agree with everything Greg wrote. Except I also agree with some of the criticisms, in that, I certainly believe it's possible to put some better metrics into the equation and come up with a better output. Or - more precisely - I think the model could use some uncertainty fuzziness baked into it, so long as it's mathematically-based uncertainty. And that is beyond my capabilities.

So if anyone wants to contribute any formulas, code or ideas to what we're doing on CHN - feel free. All ears.

I'm pretty sure this playoffstatus predictor is heavily flawed. It does not appear to sufficiently account for the inherent variance of a hockey game and considers a good team losing to a lesser team an extremely unlikely event. For example, it gives Cornell a 96% chance of making Lake Placid, which is obviously absurd. It also gives Cornell a 71% chance of getting the 1-seed in the ECAC and Clarkson a 27% chance, despite only one point separating them with eight games remaining and the two teams playing each other one more time. (Plus the game is at Clarkson and Clarkson crushed us the last time we played, which I assume the model doesn't take into account.)

Can’t agree more. These “odds” sites that calculate and blend data down for any league you can think of really don’t have any insight or context baked in.

They're also not really designed to predict the probability of a particular outcome - they're designed to predict the probability of a particular outcome assuming everything between now and then pretty much goes the way it's gone up until now.

I don't agree at all with any of this line of criticism. Roughly in order:

1. Just because intuitions disagree with odds doesn't mean the odds are wrong or the methodology is flawed.

2. We operate with a host of perception biases and our monkey brains are notoriously terrible at assigning relative likelihoods and proportions because we are strongly influenced by anecdotal experience.

3. A model will of course "assume things keep on going as they have been" because that's the best guess of what will happen. As long as the methodologically-correct degree of uncertainty (error) is built into the model, it's doing its job right.

Why is a 96% chance of making Lake Placid "obviously" absurd? Sure, it seems high, but what it means is 19 times out of 20 team x with our profile would advance. That's still once in 20 that it doesn't. That may well be in accord with historical actuals.

The problem with models isn't modeling per se -- modeling works really well or Armstrong wouldn't have hit the moon. What matters is taking care in choosing metrics and getting the probabilities right. Statistics and probability theory have been working on each of those tasks respectively for a hundred years and as uncomfortable as it may be they now do a much, much better job of predicting than the eye test or common sense.

KGR11My big problem with playoffstatus is that their methodology isn't clear. How can I agree or disagree without knowing how they did it?

IIRC, CHN does a Monte Carlo analysis based on KRACH. I'm on board with that.

That is correct. I take the two KRACH values, and just use a random number generator to get the winner for that game, and every game. Then run it around 50,000 times, or as much as possible overnight. But I do agree that KRACH might exaggerate things at the margins, given the relatively small sample sizes of past results we're dealing with.

KGR11My big problem with playoffstatus is that their methodology isn't clear. How can I agree or disagree without knowing how they did it?

IIRC, CHN does a Monte Carlo analysis based on KRACH. I'm on board with that.

That is correct. I take the two KRACH values, and just use a random number generator to get the winner for that game, and every game. Then run it around 50,000 times, or as much as possible overnight. But I do agree that KRACH might exaggerate things at the margins, given the relatively small sample sizes of past results we're dealing with.

I agree that using Adam's stated methodology is probably the best available way to look at it. However, based upon last year, I do still believe there may be some flaws in the programming of the model. Last year the model said we had a 98% chance of making the NCAA's going into the Clarkson series. We had a 35% chance of losing Game 1 to Clarkson. When we lost Game 1, our NCAA odds dropped to 65% per the model. While I realize that there were other results that Friday night, if we had a 35% chance of being at 65% after the game, there's no way our odds before the game should have been any higher than 88%, and certainly not 98%. If 98% were truly correct, than the 35% chance of a loss should have only dropped us to 94% at an average (35% of 94 plus 65% of 100 = 98).
Adam - it might be worthwhile looking into how the model handles playoff rounds and that fact that some series may go two games while others go three. Does it automatically generate the third game only when necessary? And does it appropriately handle subsequent match-ups?

"The outcome of each game in each simulation is determined by random draw, with the probability of victory for each team set by their relative KRACH ratings. So, if the simulation set included a contest between team A with KRACH 300 and team B with KRACH 100, team A will win the game in very close to 75% of the simulations. I don’t simulate ties or home ice advantage."

jfeath17
"The outcome of each game in each simulation is determined by random draw, with the probability of victory for each team set by their relative KRACH ratings. So, if the simulation set included a contest between team A with KRACH 300 and team B with KRACH 100, team A will win the game in very close to 75% of the simulations. I don’t simulate ties or home ice advantage." Do the KRACH rating update after each game? Or do you take today’s number and hold constant?

Trotsky
I don't agree at all with any of this line of criticism. Roughly in order:

1. Just because intuitions disagree with odds doesn't mean the odds are wrong or the methodology is flawed.

No one is arguing this. But sometimes the odds are so, for lack of a better term, at odds with what we perceive to be true that heavy skepticism is warranted.

2. We operate with a host of perception biases and our monkey brains are notoriously terrible at assigning relative likelihoods and proportions because we are strongly influenced by anecdotal experience.

Even my monkey brain can see that of our four games against our most likely second round opponents, Quinnipiac and Princeton, three of those games could have gone either way. The first Q game was decided on a crazy fluke goal. We were outshot 29-20. In the second game against Quinnipiac, we again won by one goal and were outshot 28-20. The first Princeton game we were outshot 25-22 and won on a goal with under seven minutes left. I put a lot of stake in models, far more than I do in my or any "expert's" "analysis," but this particular model is flawed. And as jkahn pointed out, it yields mathematically inconsistent results in addition to failing the eye test.

3. A model will of course "assume things keep on going as they have been" because that's the best guess of what will happen. As long as the methodologically-correct degree of uncertainty (error) is built into the model, it's doing its job right.

Why is a 96% chance of making Lake Placid "obviously" absurd? Sure, it seems high, but what it means is 19 times out of 20 team x with our profile would advance. That's still once in 20 that it doesn't. That may well be in accord with historical actuals.

A math major should check me on this, but I believe having a 96% chance of winning a best-of-three series requires having an 88% chance of winning a single game. Even if Cornell were to finish the regular season as the best team in the country, I have a very hard time believing it would win almost 9/10 games against a middle-of-the-pack team. But we don't even know where the Red will finish.

The problem with models isn't modeling per se -- modeling works really well or Armstrong wouldn't have hit the moon. What matters is taking care in choosing metrics and getting the probabilities right. Statistics and probability theory have been working on each of those tasks respectively for a hundred years and as uncomfortable as it may be they now do a much, much better job of predicting than the eye test or common sense.

KGR11My big problem with playoffstatus is that their methodology isn't clear. How can I agree or disagree without knowing how they did it?

IIRC, CHN does a Monte Carlo analysis based on KRACH. I'm on board with that.

That is correct. I take the two KRACH values, and just use a random number generator to get the winner for that game, and every game. Then run it around 50,000 times, or as much as possible overnight. But I do agree that KRACH might exaggerate things at the margins, given the relatively small sample sizes of past results we're dealing with.

I agree that using Adam's stated methodology is probably the best available way to look at it. However, based upon last year, I do still believe there may be some flaws in the programming of the model. Last year the model said we had a 98% chance of making the NCAA's going into the Clarkson series. We had a 35% chance of losing Game 1 to Clarkson. When we lost Game 1, our NCAA odds dropped to 65% per the model. While I realize that there were other results that Friday night, if we had a 35% chance of being at 65% after the game, there's no way our odds before the game should have been any higher than 88%, and certainly not 98%. If 98% were truly correct, than the 35% chance of a loss should have only dropped us to 94% at an average (35% of 94 plus 65% of 100 = 98).
Adam - it might be worthwhile looking into how the model handles playoff rounds and that fact that some series may go two games while others go three. Does it automatically generate the third game only when necessary? And does it appropriately handle subsequent match-ups?

Actually, I believe based on last year's conversation about this very situation, I did find a small flaw in the algorithm, and fixed it. I might have even talked about it here. I think that brought Cornell's odds down from 98% to something more like 92 -- but I can't remember exactly. I'm sure we could find it.

Trotsky
I don't agree at all with any of this line of criticism. Roughly in order:

1. Just because intuitions disagree with odds doesn't mean the odds are wrong or the methodology is flawed.

No one is arguing this. But sometimes the odds are so, for lack of a better term, at odds with what we perceive to be true that heavy skepticism is warranted.

2. We operate with a host of perception biases and our monkey brains are notoriously terrible at assigning relative likelihoods and proportions because we are strongly influenced by anecdotal experience.

Even my monkey brain can see that of our four games against our most likely second round opponents, Quinnipiac and Princeton, three of those games could have gone either way. The first Q game was decided on a crazy fluke goal. We were outshot 29-20. In the second game against Quinnipiac, we again won by one goal and were outshot 28-20. The first Princeton game we were outshot 25-22 and won on a goal with under seven minutes left. I put a lot of stake in models, far more than I do in my or any "expert's" "analysis," but this particular model is flawed. And as jkahn pointed out, it yields mathematically inconsistent results in addition to failing the eye test.

3. A model will of course "assume things keep on going as they have been" because that's the best guess of what will happen. As long as the methodologically-correct degree of uncertainty (error) is built into the model, it's doing its job right.

Why is a 96% chance of making Lake Placid "obviously" absurd? Sure, it seems high, but what it means is 19 times out of 20 team x with our profile would advance. That's still once in 20 that it doesn't. That may well be in accord with historical actuals.

A math major should check me on this, but I believe having a 96% chance of winning a best-of-three series requires having an 88% chance of winning a single game. Even if Cornell were to finish the regular season as the best team in the country, I have a very hard time believing it would win almost 9/10 games against a middle-of-the-pack team. But we don't even know where the Red will finish.

The problem with models isn't modeling per se -- modeling works really well or Armstrong wouldn't have hit the moon. What matters is taking care in choosing metrics and getting the probabilities right. Statistics and probability theory have been working on each of those tasks respectively for a hundred years and as uncomfortable as it may be they now do a much, much better job of predicting than the eye test or common sense.

I love models. This particular model just isn't very good.

I checked your math, 88% for a single game is correct. But if we're the #1 team in the ECAC, we wouldn't be playing against the middle of the pack; we'd be playing against the worst team left, so the highest team we'd play is #8. On average, we're probably playing #9.

It sounds like Bearlover would prefer a model that incorporated more context on the games played. I'm imagining is some kind of weighted Scoring margin where you weight each goal for based on how good the opponents defense is and each goal against based on how opponents offense is. Not sure how easy that is to create, though.

KGR11
I checked your math, 88% for a single game is correct. But if we're the #1 team in the ECAC, we wouldn't be playing against the middle of the pack; we'd be playing against the worst team left, so the highest team we'd play is #8. On average, we're probably playing #9.

Sorry, I meant "middle of the pack" as in the PWR, not the ECAC, because I was talking about us being the best team in the country (which is about where the PWR has us now), not the best team in the ECAC.

KGR11
It sounds like Bearlover would prefer a model that incorporated more context on the games played. I'm imagining is some kind of weighted Scoring margin where you weight each goal for based on how good the opponents defense is and each goal against based on how opponents offense is. Not sure how easy that is to create, though.

I'd love a model like that, though that's not my biggest gripe with this model. Rather, the clearest problem is that the model does not sufficiently account for the natural randomness of a hockey game. It apparently treats slight favorites as big favorites, big favorites as overwhelming favorites, etc. Others in this thread have argued that maybe those big favorites are big favorites, and that the #1 seed in the ECAC is overwhelmingly likely to beat a team that's 30th in the PWR, but I have never seen odds for a hockey game even come close to assigning one team an 88% chance of winning. Someone who gambles should verify, but I would wager there hasn't been an NHL game this season where the odds were more than 70% in one direction.

Re-linking to this article, which states: " the better NHL team can expect to win 57% of matches played against an opponent on neutral ice."

It is true that there is a greater disparity between NCAA teams than there is between NHL teams, but 88% against an average team is just nuts.

KGR11
I checked your math, 88% for a single game is correct. But if we're the #1 team in the ECAC, we wouldn't be playing against the middle of the pack; we'd be playing against the worst team left, so the highest team we'd play is #8. On average, we're probably playing #9.

Sorry, I meant "middle of the pack" as in the PWR, not the ECAC, because I was talking about us being the best team in the country (which is about where the PWR has us now), not the best team in the ECAC.

KGR11
It sounds like Bearlover would prefer a model that incorporated more context on the games played. I'm imagining is some kind of weighted Scoring margin where you weight each goal for based on how good the opponents defense is and each goal against based on how opponents offense is. Not sure how easy that is to create, though.

I'd love a model like that, though that's not my biggest gripe with this model. Rather, the clearest problem is that the model does not sufficiently account for the natural randomness of a hockey game. It apparently treats slight favorites as big favorites, big favorites as overwhelming favorites, etc. Others in this thread have argued that maybe those big favorites are big favorites, and that the #1 seed in the ECAC is overwhelmingly likely to beat a team that's 30th in the PWR, but I have never seen odds for a hockey game even come close to assigning one team an 88% chance of winning. Someone who gambles should verify, but I would wager there hasn't been an NHL game this season where the odds were more than 70% in one direction.

Re-linking to this article, which states: " the better NHL team can expect to win 57% of matches played against an opponent on neutral ice."

It is true that there is a greater disparity between NCAA teams than there is between NHL teams, but 88% against an average team is just nuts.

I think the easiest methodology would be to analyze how KRACH's pseudo-win-loss records match up with what actually happens. I'm imagining a dampening factor or equation could make it a better predictor.

KGR11
I checked your math, 88% for a single game is correct. But if we're the #1 team in the ECAC, we wouldn't be playing against the middle of the pack; we'd be playing against the worst team left, so the highest team we'd play is #8. On average, we're probably playing #9.

Sorry, I meant "middle of the pack" as in the PWR, not the ECAC, because I was talking about us being the best team in the country (which is about where the PWR has us now), not the best team in the ECAC.

KGR11
It sounds like Bearlover would prefer a model that incorporated more context on the games played. I'm imagining is some kind of weighted Scoring margin where you weight each goal for based on how good the opponents defense is and each goal against based on how opponents offense is. Not sure how easy that is to create, though.

I'd love a model like that, though that's not my biggest gripe with this model. Rather, the clearest problem is that the model does not sufficiently account for the natural randomness of a hockey game. It apparently treats slight favorites as big favorites, big favorites as overwhelming favorites, etc. Others in this thread have argued that maybe those big favorites are big favorites, and that the #1 seed in the ECAC is overwhelmingly likely to beat a team that's 30th in the PWR, but I have never seen odds for a hockey game even come close to assigning one team an 88% chance of winning. Someone who gambles should verify, but I would wager there hasn't been an NHL game this season where the odds were more than 70% in one direction.

Re-linking to this article, which states: " the better NHL team can expect to win 57% of matches played against an opponent on neutral ice."

It is true that there is a greater disparity between NCAA teams than there is between NHL teams, but 88% against an average team is just nuts.

I think the easiest methodology would be to analyze how KRACH's pseudo-win-loss records match up with what actually happens. I'm imagining a dampening factor or equation could make it a better predictor.

Does anyone know if this has been tried?

I don't know if this has been tried, but it's a way to address the real modeling flaw here (if you even feel like it's a flaw worth addressing - there's a valid case to be made that this simulated odds thing is simply an extension of KRACH and therefore using all of their assumptions is, in fact, appropriate and whatever "bad" predictions come out are mainly a matter of academic interest).

The basic issue here is the model is taking KRACH predictors, which have some error associated with them, and then taking them as perfectly correct. It basically strips out the variance around the inputs, which leads to these kind of ridiculously overconfident predictive values. My guess is the distributions around those predictions are artificially small as a result, which is how Cornell can get 96% to make Placid.

Adding in an adjustment for KRACH's previously observed error is one option, although it's risky. We don't really know if KRACH's predictions are systematically biased with respect to the empirical reality of college hockey (intuitively, I expect this is the case, but it'd take quite a bit of data to figure that out).

Another option is to take KRACH as-is and update the model with additional information, similar to the way 538 does their CARMElo rankings for the NBA. In 538's case they have a ton of data to work with so they use player level predictors. For college hockey you might be stuck modifying by close (or even strength) possession in previous matchups and using that to adjust the KRACH-generated odds in the simulation.

Three of the four regions are drive-able; Allentown is a day trip from Ithaca. Allentown and Bridgeport are day trips for metro NYC alumni depending on whether you live in NJ/ NY or NY/CT. Worcester is great for Boston alumni. Yes, the brackets as they read now have Cornell in a bracket that looks like a sure trip to the final four, which means we're in trouble.

I'm contractually obligated to point out that South Dakota isn't North Dakota, and as NoDak is only in 12th right now, there's some hope they fall out of consideration and we have a Nazi free Sioux Falls regional.

I'm contractually obligated to point out that South Dakota isn't North Dakota, and as NoDak is only in 12th right now, there's some hope they fall out of consideration and we have a Nazi free Sioux Falls regional.

I would rather that they continue to win. If they drop to 13th or 14th, then they can't play St. Cloud or Denver in the first round. That means that either we or Notre Dame will have to go out to Sioux Falls to play them. If we're not #1, then it'll likely be us.

I'm contractually obligated to point out that South Dakota isn't North Dakota, and as NoDak is only in 12th right now, there's some hope they fall out of consideration and we have a Nazi free Sioux Falls regional.

I would rather that they continue to win. If they drop to 13th or 14th, then they can't play St. Cloud or Denver in the first round. That means that either we or Notre Dame will have to go out to Sioux Falls to play them. If we're not #1, then it'll likely be us.

Do they get to stay in Sioux Falls as a host or something? Would there be any chance that they get shipped East as a 4?

I'm contractually obligated to point out that South Dakota isn't North Dakota, and as NoDak is only in 12th right now, there's some hope they fall out of consideration and we have a Nazi free Sioux Falls regional.

I would rather that they continue to win. If they drop to 13th or 14th, then they can't play St. Cloud or Denver in the first round. That means that either we or Notre Dame will have to go out to Sioux Falls to play them. If we're not #1, then it'll likely be us.

Do they get to stay in Sioux Falls as a host or something? Would there be any chance that they get shipped East as a 4?

Because Sioux Falls is like six hours from Grand Forks.

They're host. They bought the right to stay. Which is bullshit, but that's a different topic.

I'm contractually obligated to point out that South Dakota isn't North Dakota, and as NoDak is only in 12th right now, there's some hope they fall out of consideration and we have a Nazi free Sioux Falls regional.

I would rather that they continue to win. If they drop to 13th or 14th, then they can't play St. Cloud or Denver in the first round. That means that either we or Notre Dame will have to go out to Sioux Falls to play them. If we're not #1, then it'll likely be us.

Do they get to stay in Sioux Falls as a host or something? Would there be any chance that they get shipped East as a 4?

Because Sioux Falls is like six hours from Grand Forks.

They're host. They bought the right to stay. Which is bullshit, but that's a different topic.

I'm contractually obligated to point out that South Dakota isn't North Dakota, and as NoDak is only in 12th right now, there's some hope they fall out of consideration and we have a Nazi free Sioux Falls regional.

I would rather that they continue to win. If they drop to 13th or 14th, then they can't play St. Cloud or Denver in the first round. That means that either we or Notre Dame will have to go out to Sioux Falls to play them. If we're not #1, then it'll likely be us.

NCAA seeding & placement guidelines
In setting up the tournament, the committee begins with a list of priorities to ensure a successful tournament on all fronts, including competitive equity, financial success and the likelihood of a playoff-type atmosphere at each regional site. For this model, the following is a basic set of priorities:

Cornell benefits the "financial success and the likelihood of a playoff-type atmosphere" in Allentown especially, also Bridgeport or even Worcester. I would attend any of those sites, not sure I'd fly to the Dakotas. Cornell might get 2,000 fans (more?) to Allentown.

I'm contractually obligated to point out that South Dakota isn't North Dakota, and as NoDak is only in 12th right now, there's some hope they fall out of consideration and we have a Nazi free Sioux Falls regional.

I would rather that they continue to win. If they drop to 13th or 14th, then they can't play St. Cloud or Denver in the first round. That means that either we or Notre Dame will have to go out to Sioux Falls to play them. If we're not #1, then it'll likely be us.

Do they get to stay in Sioux Falls as a host or something? Would there be any chance that they get shipped East as a 4?

Because Sioux Falls is like six hours from Grand Forks.

They're host. They bought the right to stay. Which is bullshit, but that's a different topic.

Scersk '97The tix for Allentown are cheap. (Lowest bracket is $44.50 for both days, I think; Bridgeport is $70 plus fees.)

I doubt that even matters. We're talking about hotel and for many people airfare, or at least all the associated costs of a long car trip. The actual ticket price is in the noise.

I wouldn't mind them driving the ticket prices through the roof except for the blocks reserved for the participants (which should be larger). Whatever is needed to take care of the team fans first, before catering to locals or some asshole who wants to entertain his clients.

Allentown is not pushing the tickets locally very hard. Maybe one or two ads at the arena during the game and one ad between periods on the local telecast.

Those ticket prices sound comparable to Phantoms tix. FYI, add $6/game for parking. At least that's what they charge for the Phantoms games. And no on the street parking available unless you can feed quarters into a meter.

I bought tickets for the regional in Albany two years ago. They were unable to be re-sold then and I doubt that has changed regarding tickets for regionals (which often don't sell out anyway). Frozen Four tickets are a different story.

NYC to Bridgeport is a 90 minute train ride for under $20, and you can walk to the arena from the station. Also accessible from Boston/Providence via Amtrak. Long Island via Ferry. And parking is under I-95 for the drivers. (Or rather, parking is ON I-95 most of the time).

I can get to either Bridgeport or Worcester in an hour. I would also be excited for Allentown, since I lived there while on an internship/co-op in the '90s. I'd love to see all the changes.

NYC to Bridgeport is a 90 minute train ride for under $20, and you can walk to the arena from the station. Also accessible from Boston/Providence via Amtrak. Long Island via Ferry. And parking is under I-95 for the drivers. (Or rather, parking is ON I-95 most of the time).

I can get to either Bridgeport or Worcester in an hour. I would also be excited for Allentown, since I lived there while on an internship/co-op in the '90s. I'd love to see all the changes.

Oh yeah - this is the area where I usually give Jim grief, not the polls .... I just cannot stand - for decades at this point - the idea of posting "bracketology" articles based on "what it would be if the season ended today" - because ...... it doesn't end today. I don't see the point in the exercise.

But by all means - keep posting it - don't mean to stop you

FWIW ... I posted an article yesterday where, as I do each year, just write about the different possibilities and caveats. I do make a projection, but at least it's based upon The Matrix, which plays out the rest of the season.

Oh, great, now there's two regional hosts who might get de facto home games against unlucky much higher seeds.

This is such a fucked-up system!!

I have a feeling our attendance would be significantly higher than psu. I would take it.

I have the opposite feeling. It'd probably be a fun atmosphere. But just win, baby.

Good question. No idea whether Pedo State travels for hockey.

As Beeeej said it's a fucked up system. If we're going to worry so much about $$$ that we cheat for the hosts to ensure attendance I'd rather just chuck the regionals and go to a straight 16 team field with the 1R and QF at home sites best-of-3, no worries about intraconference. There has never been a men's NC$$ game at Lynah.

They don't need to travel so much as that there's bazillions of sports-crazed Penn State grads littered throughout the state. When Penn State has games at the Wells Fargo Center (the big arena in Philly) there are usually about 10,000 Penn State people there going nuts, even though it's 3 hours away. And it's not travelling students.

Plus, Penn State has had a head start on ticket sales, knowing they are going to be there (if they make it). That said, Cornell fans have a much greater opportunity to buy tix and travel to Allentown than Sioux Falls. And as good as Penn State's following may be in Pennsylvania, it would not match the sheer lunacy of North Dakota fans - who have already sold out Sioux Falls and will be loud. Heck, North Dakota got 8,000 people or so to show up for a mid-season game in New York City.

They don't need to travel so much as that there's bazillions of sports-crazed Penn State grads littered throughout the state. When Penn State has games at the Wells Fargo Center (the big arena in Philly) there are usually about 10,000 Penn State people there going nuts, even though it's 3 hours away. And it's not travelling students.

Plus, Penn State has had a head start on ticket sales, knowing they are going to be there (if they make it). That said, Cornell fans have a much greater opportunity to buy tix and travel to Allentown than Sioux Falls. And as good as Penn State's following may be in Pennsylvania, it would not match the sheer lunacy of North Dakota fans - who have already sold out Sioux Falls and will be loud. Heck, North Dakota got 8,000 people or so to show up for a mid-season game in New York City.

The Sioux are North Dakota's only professional sports team. Their travel contingent is the equivalent of Packers or Vikings fans. It's amazing. Minny and Wisco are impressive but NoDak has to be the most crazy travel contingent I've ever seen.

Point taken on Pedo State. We don't need any of that if we can avoid it by getting to Worcester or Bridgeport.

But for the moment, just win baby. "You gotta take it one game at a time and the Good Lord willing things will work out."

TrotskyPoint taken on Pedo State. We don't need any of that if we can avoid it by getting to Worcester or Bridgeport.

If I'm Cornell, I prefer Allentown. For one, Penn State might not even make it. For two, it's much closer from Ithaca or NYC to Allentown than Worcester/Bridgeport is. Don't worry about the PSU fans. Cornell can flood the place just the same, if it wants to. And if it can't, then shame on the Faithful.

Oh, great, now there's two regional hosts who might get de facto home games against unlucky much higher seeds.

This is such a fucked-up system!!

I have a feeling our attendance would be significantly higher than psu. I would take it.

you do not know penn state. they are huge and they are dedicated if the program is any good. if we play penn state at the garden again it will be MUCH harder to get tickets now that the program is more established.

adamw
Oh yeah - this is the area where I usually give Jim grief, not the polls .... I just cannot stand - for decades at this point - the idea of posting "bracketology" articles based on "what it would be if the season ended today" - because ...... it doesn't end today. I don't see the point in the exercise.

But by all means - keep posting it - don't mean to stop you

FWIW ... I posted an article yesterday where, as I do each year, just write about the different possibilities and caveats. I do make a projection, but at least it's based upon The Matrix, which plays out the rest of the season.

Oh, great, now there's two regional hosts who might get de facto home games against unlucky much higher seeds.

This is such a fucked-up system!!

I have a feeling our attendance would be significantly higher than psu. I would take it.

you do not know penn state. they are huge and they are dedicated if the program is any good. if we play penn state at the garden again it will be MUCH harder to get tickets now that the program is more established.

I’m friends with close to a dozen psu alum. They are all football nuts. When it comes to their hockey team, I am the one keeping them informed. They are all clueless on how their hockey team is doing.

I follow Cornell hockey more than any other Cornell sport (as many here also do), but I know what other teams are doing well and, more commonly, not so well.